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Cluster-Based Distributed Face Tracking in Camera Networks

delete2010-10-01
delete17
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OA
AI
J
Josiah Yoder *
H
Henry Medeiros
J
Johnny Park
A
Avinash C. Kak
DOI:10.1109/TIP.2010.2049179delete
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Abstract

Abstract

En 中文
In this paper, we present a distributed multicamera face tracking system suitable for large wired camera networks. Unlike previous multicamera face tracking systems, our system does not require a central server to coordinate the entire tracking effort. Instead, an efficient camera clustering protocol is used to dynamically form groups of cameras for in-network tracking of individual faces. The clustering protocol includes cluster propagation mechanisms that allow the computational load of face tracking to be transferred to different cameras as the target objects move. Furthermore, the dynamic election of cluster leaders provides robustness against system failures. Our experimental results show that our cluster-based distributed face tracker is capable of accurately tracking multiple faces in real-time. The overall performance of the distributed system is comparable to that of a centralized face tracker, while presenting the advantages of scalability and robustness.
Keywords:
Camera networks
distributed tracking
face tracking
object detection
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Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

Purdue University System cover
Purdue University System
Scholars:
3.9W
Papers: 3.6W
Citations: 66